GraemeKnowlesWMG Slide 1

Variability Reduction &A Six Sigma Process

The Basics of A Revolutionary Approach to Business

Improvement

GraemeKnowlesWMG Slide 2

Variation

qOccurs everywhere:

§ Machined dimensions

§ Time to complete a task

§ Number of faults per vehicle

§ The weight of a dispensed product

GraemeKnowlesWMG Slide 3

Leave It To The Inspectors

q Expensiveq Too lateq Not 100% effectiveq Little opportunity

for improvement

q Who is responsible for quality?

GraemeKnowlesWMG Slide 4

Are You Common or Special?

qCommon Causes§ Affect, to some extent, all

products of a process§ Inherent in the system§ Affects capability but not

predictability

qExamples§ Raw material variation§ Ambient temperature variation§ Operator variability

§ Play in a machine

qSpecial Causes§ Affect only some products of a

process§ Transient in nature§ Affects both predictability and

capability

qExamples§ Poorly trained operator§ Defective Material§ Wrong processing conditions§ Machine malfunction

GraemeKnowlesWMG Slide 5

Reducing Variation

qThe difference between Common and Special Causes lies in their effect on the process and how we tackle them

qCommon cause variation§ These affect capability but not predictability

§ Reducing their effect usually involves fundamental action on the process (process management)

qSpecial cause variation§ These affect stability and predictability

§ They can sometimes be eliminated by local action

GraemeKnowlesWMG Slide 6

The Concept of Statistical Control (I)q In Statistical Control§ For a process where only common cause variation is

present, the pattern of variation will be stable.§ This is known as being ‘In Statistical Control’.§ We can use this fact to predict, within limits, the future

results of the process.M e a n s C h a rt

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1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30

S a m p le

U C L

L C L

GraemeKnowlesWMG Slide 7

The Concept of Statistical Control (II)

q Out of Statistical Control§ When special cause variation is present, the process is not

predictable.§ This state is described as being ‘Out of Statistical Control’.

UCL

LCL

GraemeKnowlesWMG Slide 8

Establishing Control

qThe Average Chart§ Concerned with between

subgroup variation long term variation in process average

§ Control limits are calculated based on the average within subgroup variation (from R chart)

§ ‘Is process average variability excessive?’

qThe Range Chart§ Concerned with within

subgroup variation (short term variability in process spread)

§ Control limits are based on the average within subgroup variation

§ ‘Is the short term variation consistent?’

GraemeKnowlesWMG Slide 9

Can We Make It Then?

q Which process would you prefer?

q Process A cannot meet spec. q Process B could potentially

meet spec but is poorly set.q Process C is barely capable.q Process D is highly capable.q Which do you currently have?q If you don’t know, how can

you expect to succeed?

GraemeKnowlesWMG Slide 10

Process Capability

qKnowledge of capability is essential if we are to make appropriate decisions concerning the selection of processes to meet design intent

qBefore establishing its capability, the process must be stable - operating under common cause variation alone

q If the process is unstable it has indeterminate capability

GraemeKnowlesWMG Slide 11

Sigma Levels

q This measure indicates the potential of the processq An assumption within Six Sigma is that a process

centre may shift as much as 1.5 Sigma in either direction

q This gives rise to the popularly quoted 3.4 ppmdefective levels

q This is the minimum performance level when a maximum shift is applied

( )σ

σ2

LTLUTLn

−=

GraemeKnowlesWMG Slide 12

Implications of Sigma Levels

3.40.0026 sigma

2330.575 sigma

6,210634 sigma

66,8102,7003 sigma

308,70045,6002 sigma

Ppm with 1.5 sigma shiftPpm with no shiftSigma Level

Upper Tolerance

Lower Tolerance

GraemeKnowlesWMG Slide 13

Two Stage Improvement

q If process is not stable remove the special causes

to attain stability

§ SPC techniques will indicate when a special cause is present

§ Use problem solving approach and associated tools

q If process is stable but has poor capability§ Reduce variation by taking fundamental action on the process

§ Use DOE & advanced statistical techniques to optimise the process

§ It is no good looking for special causes

GraemeKnowlesWMG Slide 14

Juran’s Trilogy

q Modified from Juran’sQuality Trilogy

q The system is first planned and achieves the level of performance of which it is initially capable

q Sporadic special causes occur & should be tackled

q Fundamental improvement actions change the zone of performance to a new level

GraemeKnowlesWMG Slide 15

Six Sigma Contribution

q Six Sigma is primarily about rapid, sustainable improvements in performance.

q Resources and expertise are brought to bear on key parameters and processes where performance is not at an acceptable level.

q The new level of performance is ‘baked in’ by setting up new control mechanisms.

Per

form

ance

Lev

el

Time

Special cause

Original zoneof performance

PerformanceImprovement

New zone of performance

Planning PerformanceControl

Feedback

Six Sigma Focu

s

GraemeKnowlesWMG Slide 16

Six Sigma Definition(s)

qA measure:§ A statistical definition of how far a process deviates from

perfection

qA target:§ Equates to 3.4 ppm defective or unacceptable

qA philosophy:§ A long –term business strategy focused on the reduction

of cost through driving down variation in product and processes

GraemeKnowlesWMG Slide 17

Six Sigma Applicability

qManufacturing

qDesignqTransactional Processes

GraemeKnowlesWMG Slide 18

Key Themes of Six Sigma

Six SigmaProcess

StructuredProblemSolving

ProcessFocus

VariabilityReduction

CostDriven Team

work

CustomerFocus

WasteReduction

MeasurableBusiness Benefit

GraemeKnowlesWMG Slide 19

A Six Sigma Process

Define

Measure

Analyse

Improve

Control

ProcessCustomer requirementsOpportunityLikely benefitsPossible contributors

Current PerformanceSources of Variability

Key VariablesRelationships

Implemented solutionPredicted & tested results

Key variables controlledPlan for stabilityTraining plan

Measure of benefits achievedRecord of the process

GraemeKnowlesWMG Slide 20

Six Sigma Tools

Define

Measure

Analyse

Improve

Control

FlowchartCause & Effect

QFD FMEA

Control ChartsCapabilityAnalysis

Pareto Waste & CostAnalysis

Multi-vari Correlation

ANOVA Measurement Capability

DOE Process redeisgn

Taguchi Poke Yoka

ControlPlan

ControlCharts

Cusum

Training